How to implement the backpropagation using Python and NumPy
First published on MSDN on Jul 04, 2017 I was recently speaking to a University Academic and we got into the discussion of practical assessments for Data Science Students, One of the key principles students learn is how to implement the back-propagation neural network training algorithm.Azure Deep Learning and ND, NC series with NVidia
First published on MSDN on Dec 21, 2017 ND and NCv2 Series VMs generally availableND-Series virtual machines (VMs) are specifically designed for the needs of artificial intelligence (AI) and Deep Learning workloads, offering excellent performance for training and inference: ✓They are powered by NVIDIA Tesla P40 GPUs based on the new Pascal Architecture and provide excellent performance for FP32 (single precision floating point operations), for AI workloads utilizing CNTK, TensorFlow, Caffe, and other frameworks.Setting up more than 18 GPU Instances on Azure using VMs or Containers
First published on MSDN on Mar 14, 2017 I have been getting a number of questions around the availability of Azure N Series GPU at present we have two SKUs NC (GPU Compute}_ and NV (GPU Visualisation) This blog explains the differences between the SKUs and where NC vs NV hardware instances should be used https://blogs.Using Shibboleth and Domain Connecting your Data Science Virtual Machine
First published on MSDN on Jun 19, 2017 Installing Shibboleth and federating it with your Office365 AADA number of institutions have contact me asking how they can configure a Shibboleth server running on Windows Server or Linux.Microsoft’s Batch AI Service - Train & test machine learning models, on pools of GPU machines.
First published on MSDN on Nov 07, 2017 Microsoft Batch AIMicrosoft’s Batch AI Service is a new service that helps you train and test machine learning models, including deep learning models, on pools of GPU machines.
